Predicting Licensure Examination for Teachers (LET) Outcomes: A Regression Analysis of Mathematics Teacher Graduates' Course Performance and LET Results

Source abstract

This study employed a predictive correlational design to investigate the extent to which the performance of mathematics teacher graduates in both professional and specialization courses predicts their outcomes in the Licensure Examination for Teachers (LET). Seventy-seven (77) respondents were identified through selection criteria and power analysis. The study's findings revealed that college course performance aligned with LET outcomes. Moreover, the results indicated a distinct emphasis on intellectual skills in general education and practical skills in professional education. Procedural fluency and problem-solving skills were highlighted in specialization, particularly in mathematics content courses. The study established a correlation between college course grades and LET performance, emphasizing the significance of specific courses. Recommendations include aligning instructional practices with LET competencies, enhancing curriculum emphasis, developing outcomes-based learning activities, introducing LET-type comprehensive examinations in general, professional, and specialization courses after 3rd year in the college to enhance retention and mentoring policies, implementing regression models for predictive analysis, and providing targeted professional development specially for teachers handling courses that are significant predictors of LET performance in professional and specialization, focusing on refining instructional practices and aligning them with the competencies emphasised in the LET. A confirmatory study is suggested to validate the identified causal relationships between the students’ college course performance and LET performance and assess the effectiveness of the recommended regression models.